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ACTA HORTICULTURAE SINICA ›› 2019, Vol. 46 ›› Issue (2): 237-251.doi: 10.16420/j.issn.0513-353x.2018-0373

• Research Papers • Previous Articles     Next Articles

Fruit Character Diversity Analysis and Numerical Classification of Local Pear Germplasm Resources in Fujian

ZENG Shaomin,CHEN Xiaoming,and HUANG Xinzhong*   

  1. Fruit Research Institute,Fujian Academy of Agricultural Sciences,Research Centre for Engineering Technology of Fujian Deciduous Fruits,Fuzhou 350013,China
  • Online:2019-02-25 Published:2019-02-25

Abstract:

Twenty-six fruit characters were collected and determined from 50 local pear germplasm resources in Fujian Province. Distribution frequency,coefficient of variation,and Shannon-Weaver index were analyzed. Q cluster,R cluster and principal component analysis were used to evaluate the germplasm resources and characters. The results showed that the diversity of local pear fruit description characters was abundant. Conspicuous fruit dot,many fruit russeting,rough skin,crisp flesh,sour-sweet flavor,absent astringency,small fruit core and maturity in September had more proportion than other corresponding descriptors,accounting for 92%,52%,54%,50%,50%,70%,54% and 80%,respectively. The average variation coefficient of content of vitamin C and titratable acid,ratio of SS and TA,and ratio of TSS and TA was 67.60%,48.26%,42.22% and 41.14%,respectively,which was higher than that of other numerical characters. The fruit peel color and shape was found to have the richest diversity among 13 description characters,with 1.660 and 1.605 of Shannon-Weaver index. And the indexes of 13 numerical characters range from 1.698 to 2.074,which was higher than that of 13 description characters with 0.324 to 1.660 of Shannon-Weaver index,indicating that the numerical characters had richer diversity than description characters. Q cluster analysis showed that all the tested germplasm resources were divided into five groups at the Euclidean distance of 14.71,and there were differences of fruit characters among difference groups without regional trend. R cluster analysis showed that 26 characters closely related were significantly clustered into five groups at coefficient of 1.236. Twenty-six characters were mainly composed of 10 independent principal components with the cumulative contribution rate of 86.545%,which showed dispersion of contribution rate and multi-directional variation of local pear fruit characters. Positively increasing the first principal component factor will be favorable for improving the fruit interior quality,while positively increasing the second and fourth principal component factor will be favorable for improving the fruit exterior quality,and negatively increasing the third principal component factor will be beneficial to increase fruit size.

Key words: pear, germplasm resource, fruit, character, diversity, numerical classification

CLC Number: